Neural architecture search has attracted a lot of attention since it can automatically search for an optimized architecture for a certain task and achieve remarkable performance [1]}, [2]}, [3]}, [4]}. The optimization algorithms of neural architecture search include reinforcement learning [1]}, evolutionary algorithm, random search [6]}, and gradient-based algorithm [2]}. There is a lot of work towards reducing the computational resources required by searching, including weight sharing [1]}, progressive search, one-short mechanism [2]}, and using a proxy task. The performance of the discovered architecture by neural architecture search has surpassed human-designed architecture in many computer vision tasks, including classification [2]} and image generation [3]}.
